Resolving geographic units that do not neatly coincide is a common problem in spatial data analysis. The method outline here attempts to conflate King County Health Reporting Areas (HRAs) to US Census tracts. In the cases where a given tract is entirely within an HRA, that tract receives the HRA’s unique identifier (HRA_ID). On the other hand, in cases where a given tract overlaps multiple HRAs, block-level census data is used to determine which HRA ID to assign to the tract.
This method provides three alternatives of block-level counts that can be used:
| Count Type | Variable ID | Source |
|---|---|---|
| Population | POP |
Table P1, U.S. Census Bureau, 2010 Census |
| Housing Units | HU |
Table H1, U.S. Census Bureau, 2010 Census |
| Population in Housing Units | HUPOP |
Table H10, U.S. Census Bureau, 2010 Census |
The following actions are performed in this method:
class = SpatialPointsDataFrame)sp::over())POP,HU,POPHU) are summedAfter running the assignment algorithm, it is clear that the POP and POPHU variables result in the same HRA assignments. HU differs from the other two variables in only 3 of the 398 tracts:
| GEOID_TR | HRA_POP | HRA_POPHU | HRA_HU |
|---|---|---|---|
| 53033022202 | Kirkland North | Kirkland North | Kirkland |
| 53033025001 | Bellevue-South | Bellevue-South | Newcastle/Four Creeks |
| 53033028801 | SeaTac/Tukwila | SeaTac/Tukwila | Des Moines/Normandy Park |